Quintuple Implication Algorithms Of Fuzzy Reasoning And Multi-criteria Group Decision Making Approachs Based On SVNNs

The quintuple implication algorithms of fuzzy reasoning take the closeness between A and A^*（or B and B^*）into account.Which is more in accordance with human thinking.The single valued neutrosophic sets are more intuitive than the intuitive ones in dealing with uncertainty and inconsistency information.This paper mainly studies quintuple implica-tion algorithms of fuzzy reasoning and multi-criteria group decision mak-ing approach based on single valued neutrosophic sets.The main research contents of this thesis are outlined as follows:Firstly,we given the predicate formal representation of the quintuple implication principle solution based on the multi-type variable first-order formal system MTL?_ms.Which brings the quintuple implication principle within the logical framework and set a sound logic foundation for quintuple implication principle of fuzzy reasoning.Secondly,we investigated the robustness of interval-valued quintuple implication algorithms based on the normalized Minkowski distances and given the perturbation of the solution of the interval-valued quintuple im-plication algorithms based on three special interval value implication op-erators and prove that the quintuple implication algorithms based on the interval value?ukasiewicz implication is robust.Finally,we given a new tangent similarity based on single valued neu-trosophic sets and expand the intuitionistic fuzzy best-worst method to sin-gle valued neutrosophic sets environment,proposed the Single Valued Neu-trosophic Set Best-worst method.Which makes this approach can solve some uncertain problems that contain inconsistency information,and we proved the feasibility of the approach through a examples.